Senior Data Engineer / Architect

Overview

On Site
USD 150,000.00 - 170,000.00 per year
Full Time

Skills

Management
Data Architecture
Computer Science
Data Engineering
Amazon Web Services
Microsoft Azure
Google Cloud Platform
Google Cloud
Cloud Computing
SQL
Data Modeling
Big Data
Apache Spark
Apache Hadoop
Apache Kafka
Orchestration
Data Governance
Regulatory Compliance
Python
Scala
Java
Problem Solving
Conflict Resolution
Analytics
Machine Learning (ML)
Business Intelligence
Collaboration
Data Science
Product Management
Extract
Transform
Load
ELT
Data Warehouse
Database
Data Quality
Data Management
Mentorship
Stacks Blockchain
DICE

Job Details

JobID: 51796

Senior Data Engineer / Architect (Remote)

Pay
$150,000 - 170,000

Location
100% Remote

Summary

We are seeking a highly skilled and innovative Senior Data Engineer / Architect to lead the design, development, and management of our enterprise data infrastructure. This role offers an exciting opportunity to work at the forefront of data technology, driving business insights and strategic initiatives through scalable and robust data solutions. If you are passionate about data architecture, have a knack for problem-solving, and thrive in fast-paced environments, we want to hear from you.

Requirements
  • Bachelor's or Master's degree in Computer Science, Data Engineering, or related field
  • 8+ years of experience in data engineering, architecture, or similar roles
  • Strong expertise in cloud platforms (AWS, Azure, Google Cloud) and cloud-native data services
  • Proficiency in SQL and data modeling techniques
  • Experience with big data technologies such as Spark, Hadoop, Kafka
  • Familiarity with data pipeline orchestration tools like Airflow or Prefect
  • Knowledge of data governance, security, and compliance standards
  • Programming skills in Python, Scala, Java, or related languages
  • Excellent problem-solving and collaboration skills

Responsibilities
  • Lead the design and implementation of scalable, secure, high-performance data pipelines and architectures to support analytics, machine learning, and BI.
  • Collaborate with data science, product management, and engineering teams to understand data needs and develop solutions.
  • Develop and maintain data models, ETL/ELT processes, and data warehouses/databases following best practices.
  • Ensure data quality, integrity, and security across all platforms.
  • Evaluate and recommend new data tools and technologies.
  • Establish standards, governance, and best practices for data management.
  • Mentor junior team members and promote continuous learning.
  • Strategize to optimize data infrastructure's growth and performance.

Benefits
  • Financially strong organization operating in a booming industry.
  • Greenfield development environment with modern technology stacks.
  • Opportunity to work with smart, driven professionals.


#Dice #ZR-Pro #LI-TS1 #LI-Remote
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